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The objective of this paper is to propose a consumer-behavior-based intelligence (CBBI) model to identify market structure so as to monitor product competition. Competitive intelligence extracted from Chinese e-business clickstream data is exploited to examine the relevance of consumers' heterogeneous behavioral feedback, namely, click, tag-into-favorite, time-of-browsing, add-into-cart, and remove-from-cart, to visualize the competitive product market structure and to predict product-level sales.

Our proposed CBBI model consists of visualization and prediction, which explore e-business clickstream data. We conduct the visualization and segmentation of market structure in the form of a perceptual map by employing K-means clustering algorithm and multidimensional scaling technique. Concurrently, we developed an updated Bayesian linear regression (BLR) to predict product-level sales by considering consumers' heterogeneous feedback. Our updated BLR specifically integrated the estimated knowledge of the previous periods to verify whether product sales are period-dependent due to the consumer memory effect in e-commerce, improving the conventional BLR of diffuse prior distribution setup in terms of mean absolute error (MAE) and root mean squared error (RMSE).

Considering the performance of consumers' heterogeneous actions, the present research visualized three different segments of the competitive market structure in a perceptual map, and its horizontal axis is shown as a signal of the ascending trend of product sales. The previous five-day period was ascertained to be the best size of a time window for the consumer memory effect on product sales prediction. This hypothesis is supported by the concept that product sales are period-dependent. The results of the proposed updated BLR indicate that consumer tag-into-favorite, add-into-cart, and remove-from-cart feedback have positive impacts on product-level sales while click and time-of-browsing have the opposite effect.

While the identified competitive product market structure elaborates consumer heterogeneous feedback toward alternative product choices, this paper contributes by extending those homogeneous consumer preferences-related marketing studies. The perceptual map's configuration in respect to period-dependent product sales facilitates the effective inclusion of consumer behavior application in product sales prediction research in e-commerce. This paper helps sellers and retailers better comprehend the impacts of heterogeneous feedback and the consumer memory effect on the degree of competition in the form of product sales. The research results also offer a managerial implication about shaping the competitive edge by conducting different product management strategies in e-commerce platforms.

The purpose of this paper is to identify potential competitive relationships among brands by analyzing the dynamic clicking behavior of consumers.

Consumer sequential online click data, collected from JD.com, is used to analyze the dynamic competitive relationship between brands. It is found that the competition intensity across categories of products can differ considerably. Consumers exhibit big differences in purchasing time of durable-like goods, that is, the purchasing probability of such products changes considerably over time. The local polynomial regression model (LPRM) is used to analyze the relationship between brand competition of durable-like goods and the purchasing probability of a particular brand.

The statistical results of collective behaviors show that there is a 90/10 rule for the category durable-like goods, implying that ten percent of the brands account for 90 percent market share in terms of both clicking and purchasing behavior. The dynamic brand cognitive process of impulsive consumers displays an inverted V shape, while cautious consumers display a double V shaped cognitive process. The dynamic consumers’ cognition illustrates that when the brands capture a half of the click volume, the brands’ competitiveness reaches to its peak and makes no significant different from brands accounting for 100 percent of the click volume in terms of the purchasing probability.

There are some limitations to the research, including the limitations imposed by the data set. One of the most serious problems in the data set is that the collected click-stream is desensitized severely, restricting the richness of the conclusions of this study. Second, the data set consists of many other consumer behavioral data, but only the consumer’s clicking behavior is analyzed in this study. Therefore, in future research, the parameters brand browsing by consumers and the time of browsing in each brand should be added as indicators of brand competitive intensity.

The authors study brand competitiveness by analyzing the relationship between the click rate and the purchase likelihood of individual brands for durable-like products. When the brand competitiveness is less than 50 percent, consumers tend to seek a variety of new brands, and their purchase likelihood is positively correlated with the brand competitiveness. Once consumers learn about a particular brand excessively among all other brands at a period of time, the purchase likelihood of its products decreases due to the thinner consumer’s short-term loyalty the brand. Till the brand competitiveness runs up to 100 percent, consumers are most likely to purchase a brand and its product. That indicates brand competitiveness maintain 50 percent of the whole market is most efficient to be profitable, and the performance of costing more to improve the brand competitiveness might make no difference.

There are many studies on brand competition, but most of these research works analyze the brand’s marketing strategy from the perspective of the company. The limitation of this research is that the data are historical and failure to reflect time-variant competition. Some researchers have studied brand competition through consumer behavior, but the shortcoming of these studies is that it does not consider sequentiality of consumer behavior as this study does. Therefore, this study contributes to the literature by using consumers’ sequential clicking behavior and expands the perspective of brand competition research from the angle of consumers. Simultaneously, this paper uses the LPRM to analyze the relationship between consumer clicking behavior and brand competition for the first time, and expands the methodology accordingly.

With a fast-growing Muslim population and consumer income, the demand for halal products by Chinese Muslims has expanded strongly. However, literature addressing Chinese Muslims’ consumption is limited, and their demand for halal products is little understood. This study aims to investigate what affects Chinese Muslims’ demand for halal products, with a focus on halal personal care products.

A survey of 500 respondents was conducted to collect cross-sectional data in northwest China. Data were processed and analysed with a logit model.

Apart from faithfulness, reliability of recommendations, product price, product availability and halal authenticity are most important determinants influencing the purchase of halal products by Chinese Muslims.

In this study, the focus is only on Muslims from China’s Northwest. Due to various constraints, the cluster and convenience sampling methods are used.

The findings are invaluable for governments and industry bodies to form policies to better meet the burgeoning demand for halal products by Chinese Muslims. They are also very invaluable for producers and exporters who intend to penetrate the halal market in non-Muslim-dominant countries like China.

Studies on understanding the needs of Muslims in non-Muslim countries are limited. Given the sheer size of the Muslim population in China, understanding their demand for halal products and influential determinants concerning such demand adds to the literature and helps the industry to better serve and capitalise on the growing market.

With the development of economy and the progress of science and technology, the function of Luoyang city is constantly enriched and expanded. The city is no longer a simple area for people to live in. The function structure of the city is affected by the external factors and is constantly expanding. Urban logistics is one of the important influencing factors. To more comprehensively and accurately understand the status and role of logistics network space in urban planning, the characteristics and development law of urban logistics structure from the theoretical point of view are analyzed in this paper with Luoyang City as the research background. The city logistics function is determined as one of the main factors affecting the economic growth of the city is determined through the literature search method, consulting professionals and other research methods. Urban road planning and design are the focus of the study; the planning and development of urban logistics road network in Luoyang City are compared and analyzed. In full consideration of the necessity of the optimization of the urban logistics network space, the preliminary optimization scheme design and suggestion of Luoyang logistics is introduced. At the end of this paper, the sustainable development and the status of the future urban logistics function are analyzed and prospected. Continuous research and analysis of multiple subjects and angles are still needed.

Since most literature on international performance appraisal is derived from Western MNCs, it is questionable whether the Western theories are equally powerful when applied to other national contexts. This study develops the Chinese international performance appraisal model by exploring performance appraisal policies and practices and the associated factors in Chinese MNCs. It reveals that Chinese MNCs adopt different approaches towards different groups, particularly different nationalities and managerial status. The Chinese international performance appraisals are a mix of home and local appraisal systems, and a mix of traditional Chinese personnel management and modern Western HRM concepts. Moreover, Chinese international performance appraisal policies and practices are affected by various host‐contextual and firm‐specific factors, and there is also an interplay between international performance and other international human resource management activities.

The purpose of this paper is to examine the drivers, practices, and outcomes of social media use in the management of organizational supply chain.

Online questionnaire survey was used to collect data from 285 organizations representing different industries in China. The data then were analyzed with structure equation modeling using SmartPLS.

The results indicate that key antecedents such as external pressures, internal readiness, expected benefits, strategic goals, and perceived risks influence organizational social media use, which subsequently impact organizational performance outcomes in operation and marketing as well as the satisfaction level of both internal and external constituents, such as customers, employees, partners, and suppliers.

The study obtained data about one organization from only one respondent and did not used random sampling.

This study provides insights on why and how companies should use social media for relationship building and business outcomes.

Drawing from the resources-based view, social networks, strategic choice theory, and technology organization and environment framework, a new social media utilization model for business outcome was established and testified using empirical data. This study is one of the first studies that adopts technology-organization-environment (TOE) framework of technology adoption theory to study organizational social media use. The findings in this study confirm the validity of the TOE framework for analyzing social media adoption and use in various organizations.

The paper aims to contribute to the current research on China's Belt and Road Initiative (BRI) from a historical point of view. The paper investigates why the history of the Silk Roads is important to the BRI, what is in the guiding thought underpinning China's Silk Roads narrative and how this narrative is presented transnationally, through an insightful analysis of the Communist Party of China's (CPC) view of the Silk Roads history, as well as its perception of the connections between the Silk Roads history and the BRI.

The paper sits in the interface between history, heritage and state power. The argument is framed in concepts of historical constructionism and soft power. It is based on the discourse analysis of China's official narrative of Silk Roads and a case study of the planning for the World Heritage nomination of the Maritime Silk Routes (MSR) (China section). The case study is conducted through a qualitative analysis of academic publications, media reports and programs, official speeches and documents that are available to the public in hardcopy or on the Internet.

The paper reveals the relationship between the state-endorsed Silk Roads narrative and the BRI. The paper argues that the state-backed Silk Roads narrative as well as the planning for the World Heritage nomination of the MSR (China section) is guided by the Chinese Communist Party's perception of the BRI. In this respect, the Silk Roads-associated history, heritage and memory are shaped and deployed to serve as a convenient platform for the promotion of the BRI. The Party leaders' perception of the BRI is in large part about the revival of China's past glory, its national rejuvenation and the demonstration of China's soft power.

The paper contributes to the existing literature on the BRI through its enquiries into how the CPC reconcile nationalist ambitions with notions of peace, harmony and cosmopolitanism and how CPC's view of the Silk Roads history shapes its vision of the BRI. The paper examines the role of the state in the construction and articulation of the Silk Roads-associated history, heritage and memory. It investigates how China's official interpretation of the Silk Road heritage serves China's BRI.

This paper aims to successfully synthesize three-dimensional spindle-like Au functionalized Co₃O₄-ZnO nanocomposites; characterize the structure, morphology and surface chemical properties of the products; study the effect of Au NPs doping concentration, operating temperature different gas to, sensing properties; and introduce an attractive gas sensor for acetone detection.

Au NPs functionalized Co₃O₄-ZnO nanocomposite was prepared by coprecipitation and impregnation methods; the structure and surface chemical property of the products were characterized by XRD, SEM, TEM, UV-Vis, BET and XPS. The sensing ability of Au@Co₃O₄-ZnO for acetone and mechanism was analyzed systematically.

The results of gas sensing tests show that the unique component structure, Schottky junction and catalytic effect of Au functionalization make it have low operating temperature, excellent selectivity, high response (10 ppm, 56) and rapid response recovery time.

All the characterization and test data of the prepared materials are provided in this paper and reveals the gas sensing mechanism of the gas sensor.

The detection limit is 2.92–100 ppb acetone. It is promising to be applied in low-power, micro detection and miniature acetone gas sensors.

The gas sensor prepared has a lower working temperature and low detection limit, so it has promising application prospects in low-concentration acetone detection and early warning.

The unique component structure, Schottky junction and catalytic effect of Au functionalization Co₃O₄-ZnO make it have low operating temperature, excellent selectivity and rapid response recovery time.

This paper presents various available and new techniques for prediction of the hysteresis loop, no‐load current curve and hysteresis losses. It is shown that linearization is a convenient method to be employed for quick estimation of the hysteresis loop with acceptable accuracy. Although the third and fifth order functions for saturation curve prediction lead to more accurate results, it requires more data and also more complicated equations resulting in longer computation time. Use of various third and fifth order functions for saturation curve are the noticeable advantages of the techniques. The three proposed techniques could predict the hysteresis loop of transformers using simple experiments and iterative computer computations.